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In this first tutorial, you will meet your tutor, and learn a little more about the course including various important administrative and procedural details, assessments, what you can expect from the course, what is expected of you, and how to volunteer to act as a participant in psychological research conducted within the Schools of Psychology and Education. You will spend some time in this tutorial going through the course outline.
INTRODUCTION TO INTELLIGENCE AND INDIVIDUAL DIFFERENCES.
For the remainder of the tutorial we will discuss a number of issues related to the topic Intelligence. You will complete a test of intellectual ability call the Dove test and you will complete an exercise first conducted by Halla Beloff at Edinburgh University in 1.
The Dove Counterbalance Intelligence Test (from Coon, 1)
Almost everyone is curious about how they would score on an intelligence test. If you would like to get a rough estimate of your IQ, take the following self-administered test.
Time limit 5 minutes
Circle the correct answer.
1. T-bone Walker got famous for playing what?
a. Trombone
b. Piano
c. T-flute
d. Guitar
e. "hambone"
. A "gas head" is a person who has a
a. Fast-moving car
b. Stable of "lace"
c. "process"
d. habit of stealing cars
e. a long jail record for arson
. If you throw the dice and 7 is on top, what is facing down.
a. 7
b. snake eyes
c. boxcars
d. little joes
e. 11
4. Cheap chitlings (not the kind you purchase at a frozen food counter) will taste rubbery unless they are cooked long enough. How soon can you quit cooking them to eat and enjoy them?
a. 45 minutes
b. two hours
c. 4 hours
d. one week (on a low flame)
e. one hour
5. Bird or Yardbird was the jacket jazz lovers from coast to coast hung on?
a. Lester Young
b. Peggy Lee
c. Benny Goodman
d. Charlie Parker
e. Birdman of Alcatraz
6. A "handkerchief head" is
a. A cool cat
b. A porter
c. An Uncle Tom
d. A hoodi
e. A preacher
7. Jet is
a. An East Oakland motorcycle club
b. One of the gangs in West Side Story
c. A news and gossip magazine
d. A way of life for the very rich
8. "Bo Diddly" is a
a. game for children
b. down-home cheap wine
c. down-home singer
d. new dance
e. Moejoe call
. Which word is most out of place here?
a. Splib
b. Blood
c. Gray
d. Black
e. Spook
10. If a pimp is uptight with a woman who gets state aid, what does he mean when he talks about "Mother's Day"?
a. Second Sunday in May
b. Third Sunday in June
c. First of every month
d. None of these
e. First and fifteenth of every month
11. How much does a "short dog" cost?
a. 15c
b. $
c. 5c
d. 5c
e. $1.1 plus tax
1. Many people say that "Juneteenth" (June 10th) should be made a legal holiday because this was the day when
a. The slaves were freed in the United States
b. The slaves were freed in Texas
c. The slaves were freed in Jamaica
d. The slaves were freed in California
e. Martin Luther king Jr was born
f. Booker T. Washington died.
1. If a man is called a "blood", then he is
a. Fighter
b. Mexican-American
c. Black
d. Hungry hemophile
e. Red man or Indian
14. What are the Dixie Hummingbirds?
a. A part of the KKK
b. A swamp disease
c. A modern gospel group
d. A Mississippi Negro paramilitary strike force
e. Deacons
15. The opposite of square is
a. Round
b. Up
c. Down
d. Hip
e. Lame
Your tutor will provide you with the answers.
If you scored 14 on this exam, your IQ is approximately 100, indicating average intelligence. If you scored 11 or less, you are mentally retarded. With luck, and the help of a special educational program, we may be able to teach you a few simple skills!
DISCUSSION
1. This test is a little unfair. Why?
. How do you think the fairness of this test compares with other measures of IQ?
Beloff Experiment.
Please fill out the table Below. When estimating IQ scores please do not go below the 70 as a minimum and do not go above 150 as a Maximum.
My Gender is…. (circle) Male / Female
I estimate my IQ to be…
I estimate my mother's IQ to be…
I estimate my father's IQ to be…
We will collect the results of this exercise and let you know what we found next week.
WEEK - MEASURING INDIVIDUAL DIFFERENCES AND INTELLIGENCE.
This tutorial will cover measuring individual differences, measures of variability and intelligence.
1. Beloff Results and Discussion
Insert results and labels in the table below.
Own IQ estimate
Mother's IQ estimate
Father's IQ estimate
DISCUSSION
1. Did we get the same results as Beloff?
. What might be some reasons why we found the results that we did?
. Evaluation and Comparison of Scores
If we want to evaluate a subjects individual performance on two tests, say Test A and Test B, then comparing her raw score would not be particularly informative if both the tests have different means and standard deviations. For instance, a score of 0 on Test A may be the highest score, but on Test B it may be the lowest score.
Individual raw scores need to be considered in relation to the rest of the groups performance for any comparison across tests to be meaningful. That is, the raw score needs to be transformed into a new score which takes the rest of the group (or a specified comparison group, as in test norms) into account. There are two ways that raw scores can be transformed so that comparisons can be made percentile ranks and standard scores.
.1 Percentile Ranks
If an individual performance is expressed as a rank (first, third etc. in the group) we can evaluate the performance more readily than with a raw score. However, the rank score, by itself, does not take into account the size of the group. It may sound quite good if one is third in a race but not if there were only two other competitors.
Percentile ranks do take into account the size of the group. The percentile rank for a particular score indicates the percentage of the group that obtained that score or a lower score.
To obtain percentile ranks the frequency distribution of scores needs to be converted to a cumulative frequency distribution. The cumulative frequency distribution indicates for each score how many in the group have obtained at most that score. For example, consider the following table over the page
Score Frequency CumulativeFrequency Percentile Rank
10876541 564511610 50455011040 50/50 x 100 = 100%45/50 x 100 = 0%/50 x 100 = 78%5/50 x 100 = 70%0/50 x 100 = 60%1/50 x 100 = 8%10/50 x 100 = 0%4/50 x 100 = 8%/50 x 100 = 6%0/50 x 100 = 0%
The cumulative frequency (cf) column is obtained by adding each frequency successively, starting at the bottom of the frequency column. So that, for a score of or below the cf is (0 + ); for a score of or below the cf is 4 (0 + + 1); for a score of 4 or below the cf is 10 (0 + + 1 + 6) etc., until for the highest score of 10 the cf must be equal to the total number of people in the group, namely 50. In other words we can say that everybody in the group got a score of 10 or below.
These cumulative frequencies can then be expressed as a percentage of the group size by dividing each cumulative frequency by N, in this case 50, and multiplying by 100 (to turn the fraction cf / N into a percentage).
From the percentile rank column it can be seen that 60% of the group got a score of 6 or less and 78% got a score of 8 or less, etc. In other words, the larger the percentile rank the better the performance.
Note that the percentile rank is based on the percentage of the group of subjects and does not express the obtained score as a percentage of some maximum possible score. To say that a score of 5 corresponds with a percentile rank of 8% means that 8% of the people in the group obtained a score of 5 or below, not that a score of 5 is 8% of the maximum possible score.
While percentile ranks take into account group size, like ordinary ranks, they do not provide information about the size of raw score differences in what is being measured between one rank and the next. A student who comes third in a class test may have a mark which is very close to the student who came second, while the difference in scores between the first and second students may be large. A measure which does express individual performance in terms of the group size while retaining information about the size of raw score differences is the standard score.
. Standard Scores or z?Scores
A standard score expresses a raw score in terms of its distance from the mean, where this distance is measured in units of (or multiples of) the standard deviation. For example, if a distribution of scores has a = 50 and s = 10, then a raw score of 70, which is 0 scores above the mean, can also be expressed as standard deviation units above the mean, since in this case one unit of standard deviation = 10 scores, so 0 scores = x 10 = units of standard deviation. We say that a score of 70 corresponds to a z?score of + . So standard scores or z?scores indicate in standard deviation units how far above or below the mean a raw score is.
Before the mathematical formula is introduced, consider the following example. A subject obtains the following scores on Test A and Test B, the group means and standard deviations for both tests are also given
Test X S
AB 6560 5550 1510
On which test has she performed the best? In comparing the raw scores we may be tempted to conclude that Test A is the better performance because 65 is higher than 60. However, if we take into account the means and calculate deviation scores
For Test A x = X - = 65 - 55 = 10
For Test B x = X - = 60 - 50 = 10
We can see that both raw scores are the same distance from their respective means. The important question becomes how large is a deviation score of 10 relative to the size of the average amount of deviation for each group? For each test we need to evaluate the deviation distance of 10 as multiples or fractions of the standard deviation.
For Test A, since S = 15, a deviation score of 10 is equal to two thirds of a standard deviation unit (10115 /), while for Test B, since S = 10, a deviation score of 10 is equal to one unit of standard deviation (10/10 = 1). Summarising, a score of 65 on Test A is only two thirds of a standard deviation above the mean, while for Test B a score of 60 is one standard deviation above the mean. Therefore, the subjects performance on Test B, relative to the rest of the group is superior to her performance on Test A.
The above procedure is summarised by the mathematical formula for a standard score or z?score
That is, a raw score is transformed into a z?score by dividing the individuals deviation score by the group standard deviation.
In calculating the deviation score it is important that the mean is subtracted from the raw score, so that the sign (positive or negative) is in the appropriate direction. In this way a score larger than the mean will lead to a positive z?score, a below average score will lead to a negative z?score and where a score does not deviate from the mean the z?score will be zero.
Example
The mean and standard deviation for a group of scores are = 55 and SD = 6. For three subjects from the group, express their raw scores as z?scores.
Person A 47
Person B 55
Person C 6
Solution
Person A
Person B
Person C
Person As raw score is 1. standard deviations below the mean, while Cs raw score is 1. standard deviations above the mean. Person Bs raw score is the same as the mean. In other words, As performance is just as much below average as Cs is above average, while Bs performance is exactly on average.
DISCUSSION 1 Standard Scores
Find the standard score equivalent for the following scores given a mean of 45. and a standard deviation of 10.4
(a) 55
(b) 41
(c) 45.
. The Normal Curve, Percentiles and Z?Scores
If a population distribution of scores closely approximates a normal curve, then we can use some of the mathematical properties possessed by the normal curve to make statements about our population of scores. Look at Figure .7 on page 56 of your textbook Weiten to discuss normal curve, mean, median and mode.
The important concept here is that a one?to?one relationship exists between the area under the curve and the percentage of the population obtaining scores within the corresponding range.
For example, consider a normal population distribution for IQ scores where = 100 and s = 15. We can ask, for instance, what percentage of the population are likely to have IQ scores falling between 100 and 115?
To answer this we need to find the percentage of total area under the curve falling between the two scores 100 and 115. The mathematics for this is quite advanced (beyond the scope of this unit), but fortunately areas under the normal curve have been tabulated so that we can look up the area if we know the corresponding range on the horizontal axis in standard deviation units.
A score of 115 is one standard deviation above the mean of 100 (since SD = 15). The z?score equivalent of 115 is therefore +1. The tables for areas under the normal curve tell us that 4.1% of the area under the curve will fall between the mean of the distribution (z = 0) and z = +1. We can interpret this as 4.1% of the population will have IQ scores between 100 and 115.
We can also use this information to find the percentile rank corresponding to an IQ of 115. Since 50% of the population have IQ scores below 100 and 4.1% have IQ scores between 100 and 115, then adding these two percentages together, the percentile rank of 115 is 84.1%. In other words, 84.1% of people have IQ scores of 115 or below.
The important point to realise is that regardless of the mean and standard deviation of a distribution, if the scores are normally distributed then we can always say that, for instance, 5% of scores will fall between standard deviations below and above the mean (that is, between z = ? and z = + ). So with the normal curve, areas under the curve between z?score values are fixed.
If two distributions of scores are approximately normal and have the same mean and standard deviation then raw scores from each could be directly compared. However, as we have seen, when this is not the case then we convert to z?scores in order to standardise the distributions. What is meant here by standardisation is that if the original raw score distributions are transformed into z?score distributions, then these z?score distributions always have the same mean, variance and standard deviation. It can be shown algebraically that the mean of a distribution of z?scores is always zero and the variance and standard deviation are always 1.
So, when scores from distributions with different means and standard deviations are converted to z?scores, these z?scores can be directly compared because they come from distributions that have the same mean and standard deviation.
The following table gives some of the areas under the normal curve and the corresponding z scores.
Percent area under the Normal curve between the Mean and z
z .00 .01 .0 .0 .04 .05 .06 .07 .08 .0
0.0 00.00 00.40 00.80 01.0 01.60 01. 0. 0.7 0.1 0.5
0.1 0.8 04.8 04.78 05.17 05.57 05.6 06.6 06.75 07.14 07.5
0. 07. 08. 08.71 0.10 0.48 0.87 10.6 10.64 11.0 11.41
0. 11.7 1.17 1.55 1. 1.1 1.68 14.06 14.4 14.80 15.17
0.4 15.54 15.1 16.8 16.64 17.00 17.6 17.7 18.08 18.44 18.7
0.5 1.15 1.50 1.85 0.1 0.54 0.88 1. 1.57 1.0 .4
0.6 .57 .1 .4 .57 .8 4. 4.54 4.86 5.17 5.4
0.7 5.80 6.11 6.4 6.7 7.04 7.4 7.64 7.4 8. 8.5
0.8 8.81 .10 . .67 .5 0. 0.51 0.78 1.06 1.
0. 1.5 1.86 .1 .8 .64 .8 .15 .40 .65 .8
1.0 4.1 4.8 4.61 4.85 5.08 5.1 5.54 5.77 5. 6.1
1.1 6.4 6.65 6.86 7.08 7. 7.4 7.70 7.0 8.10 8.0
1. 8.4 8.6 8.88 .07 .5 .44 .6 .80 .7 40.15
1. 40. 40.4 40.66 40.8 40. 41.14 41.1 41.47 41.6 41.77
1.4 41. 4.07 4. 4.6 4.51 4.65 4.7 4. 4.06 4.1
1.5 4. 4.45 4.57 4.70 4.8 4.4 44.06 44.18 44. 44.41
1.6 44.5 44.6 44.74 44.84 44.5 45.05 45.15 45.5 45.5 45.45
1.7 45.54 45.64 45.7 45.8 45.1 45. 46.08 46.16 46.5 46.
1.8 46.41 46.4 46.56 46.64 46.71 46.78 46.86 46. 46. 47.06
1. 47.1 47.1 47.6 47. 47.8 47.44 47.50 47.56 47.61 47.67
.0 47.7 47.78 47.8 47.88 47. 47.8 48.0 48.08 48.1 48.17
.1 48.1 48.6 48.0 48.4 48.8 48.4 48.46 48.50 48.54 48.57
. 48.61 48.64 48.68 48.71 48.75 48.78 48.81 48.84 48.87 48.0
. 48. 48.6 48.8 4.01 4.04 4.06 4.0 4.11 4.1 4.16
.4 4.18 4.0 4. 4.5 4.7 4. 4.1 4. 4.4 4.6
.5 4.8 4.40 4.41 4.4 4.45 4.46 4.48 4.4 4.51 4.5
.6 4.5 4.55 4.56 4.57 4.5 4.60 4.61 4.6 4.6 4.64
.7 4.65 4.66 4.67 4.68 4.6 4.70 4.71 4.7 4.7 4.74
.8 4.74 4.75 4.76 4.77 4.77 4.78 4.7 4.7 4.80 4.81
. 4.81 4.8 4.8 4.8 4.84 4.84 4.85 4.85 4.86 4.86
.0 4.87
.5 4.8
4.0 4.7
5.0 4.7
DISCUSSION 1 The Normal Distribution
1. List the characteristics of the normal distribution curve
. Identify sociological, political and psychological variables which you believe
(a) are distributed normally
(b) are skewed positively
(c) are skewed negatively
. Given a normal distribution with a of 50 and a S of 10 find
(a) the proportion area between the mean and the following scores
60
80
40
(b) the proportion area above the following scores
50
60
40
(c) the proportion area between the following scores
60-80
40-60
0-0
DISCUSSION Standard Normal Curve
1. Three tests were given to 000 students. Shown below are Simon's scores on each of these tests along with the mean and standard deviation in each test
a) Convert each of Simons test scores to standard scores
b) On which test did Simon score highest? On which lowest?
c) Simons score in arithmetic was surpassed by how many students?
d) What assumption must be made in order to answer the preceding question?
. Use the table for Areas Under the Normal Curve to complete the following questions
Given a normal distribution based on 1000 cases with a of 50 and SD of 10, find
a) the proportion of the curve and the number of cases between the mean and the following scores
70
45
b) the proportion of the curve and the number of cases above the following scores
70
45
c) the proportion of the curve and the number of cases between the following scores
60?70
5?60
A journal article, single author
Amir, Y. (16). Contact hypothesis in ethnic relations. Psychological Bulletin, 71, 1-4.
Weinstein, N. D. (180). Unrealistic optimism about future life events. Journal of Personality and Social Psychology,, 806-80.
. A journal article, single author, title including a colon
Anastasi, A. (185). Some emerging trends in psychological measurement A fifty-year perspective. Applied Psychological Measurement,, 11-18.
. Journal articles, multiple authors
MacLeod, C., Rutherford, E., Campbell, L., Ebsworthy, G., & Holker, L. (00). Selective attention and emotional vulnerability Assessing the causal basis of their association through the experimental manipulation of attentional bias. Journal of Abnormal Psychology, 111, 107-1.
Ross, L., Amabile, T. M., & Steinmetz, J. L. (177). Social roles, social controls, and social perception processes. Journal of Personality and Social Psychology, 5, 485-44.
Johnson, M. K., & Raye, C. L. (181). Reality monitoring. Psychological Review, 88, 67-85.
4. A journal article with a title containing a question mark
Deshpande, S. P., Joseph, J., & Viswesvaran, C. (14). Does the use of student samples affect the results of studies in cross-cultural training? A meta-analysis. Psychological Reports, 74, 77-785.
5. A journal article with a title containing a person's name
Collins, B. E. (174). Four components of the Rotter internal-external scale Belief in a difficult world, a just world, a predictable world, and a politically responsive world. Journal of Personality and Social Psychology,, 81-1.
6. A journal article with a title containing a place name
Verkuyten, M., Hagendoorn, L., & Masson, K. (16). The ethnic hierarchy among majority and minority youth in The Netherlands. Journal of Applied Social Psychology, 6, 1104-1118.
7. A journal article with a title containing both a place and person's name
Lysgaard, S. (155). Adjustment in a foreign country Norwegian Fulbright grantees visiting The United States. International Social Science Bulletin, 7, 45-51.
8. A journal article with a title containing an acronym
Forgas, J. P. (15). Mood and judgment The affect infusion model (AIM). Psychological Bulletin, 117, -66.
. Multiple journal articles by the same author in the same year
Gudjonsson, G. H. (15a). The standard progressive matrices Methodological problems associated with the administration of the 1 adult sample. Personality and Individual Differences, 18, 441-44.
Gudjonsson, G. H. (15b). Raven's norms on the SPM revisited A reply to Raven. Personality and Individual Differences, 18, 447.
10. A book, single author, first edition
Dyer, C. (15). Beginning research in psychology. Oxford Blackwell.
Seligman, M. E. P. (175). Helplessness On depression, development and death. San Francisco Freeman.
11. A book, single author, later editions
Cronbach, L. J. (10). Essentials of psychological testing (5th ed.). New York HarperCollins.
Myers, D. G. (1). Social psychology (4th ed.). New York McGraw-Hill.
1. A book, multiple authors, first edition
Huck, S. W., Cormier, W. H., & Bounds, W. G. (174). Reading statistics and research. New York HarperCollins.
1. A book, multiple authors, later edition
Biehler, R. F., & Snowman, J. (1). Psychology applied to teaching (7th ed.). Boston, MA Houghton Mifflin.
14. The Diagnostic and Statistical Manual of Mental Disorders
American Psychiatric Association. (14). Diagnostic and statistical manual of mental disorders (4th ed.). Washington, DC Author.
15. A chapter in an edited book, single author, single editor
Gilbert, D. T. (15). Attribution and interpersonal perception. In A. Tesser (Ed.), Advanced social psychology (pp. -147). New York McGraw-Hill.
16. A chapter in an edited book, single author, multiple editors
Hartmann, D. P. (1). Design, measurement, and analysis Technical issues in developmental research. In M. H. Bornstein & M. E. Lamb (Eds.), Development psychology An advanced textbook (nd ed., pp. 5-154). Hillsdale, NJ Lawence Erlbaum Associates.
17. A chapter in an edited book, multiple authors, first edition
Clore, G. L., Gasper, K., & Garvin, E. (001). Affect as information. In J. P. Forgas (Ed.). Handbook of affect and social cognition (pp. 11-144). Mahwah, NJ Erlbaum.
18. A chapter in an edited book, multiple authors, later editions
Dinges, N. G., & Baldwin, K. D. (16). Intercultural competence A research perspective. D. Landis & R. S. Bhagat (Eds.), Handbook of intercultural training (nd ed., pp. 106-1). California Sage.
1. Chapter in an edited multi-volume book.
Fiske, S. T., & Pavelchak, M. A. (186) Category-based versus piecemeal-based affective responses Developments in schema-triggered affect. In R. M. Sorrentino & E. T. Higgins (Eds.), Handbook of motivation and cognition (Vol. 1, pp. 167-0). New York Guildford Press.
0. Paper presented to a conference
Roberts, R. E., Phinney, J. S., Romero, A., & Chen, Y-W. (16). The structure of ethnic identity across ethnic groups. Paper presented at the meeting of the Society for Research on Adolescence, Boston, MA.
References.
American Psychological Association. (001). Publication manual of the American psychological association (5th ed.). Washington, DC Author.
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